CN111798449A - Spinneret plate residual impurity detection method based on image technology - Google Patents
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Abstract
The invention relates to a spinneret plate residual impurity detection method based on image technology, which comprises the steps of firstly, acquiring an image of a single spinneret hole to be detected under the same acquisition condition, carrying out binarization processing on the image to obtain a binarization image a, acquiring an image of a single standard spinneret hole, carrying out binarization processing on the image to obtain a binarization image b, wherein the standard spinneret hole is a spinneret hole which has the same specification as the spinneret hole to be detected and does not contain impurities; then denoising the binary image a and the binary image b, namely removing the peripheral area of the spinneret orifice; then, adjusting the denoised binary image a to ensure that the contour boundaries of the spinneret holes in the denoised binary image a and the spinneret holes in the denoised binary image b are superposed and are positioned at the same position; and finally, calculating the impurity content and judging the position of the impurity. The method of the invention has simple operation, is suitable for spinneret orifices with various shapes, can obtain impurity content and impurity positions, and has low false detection rate.
Description
Technical Field
The invention belongs to the field of spinneret plate residual impurity detection methods, and relates to a spinneret plate residual impurity detection method based on an image technology.
Background
In the spinning production process, a spinneret plate converts a viscous-flow-state high polymer melt or solution into a thin flow with a specific cross section through micropores, and the thin flow is solidified through a solidification medium or a solidification bath to form filaments. The fine particles such as mechanical impurities, gel, carbon fibers, heat cracks and the like in the melt often block micropores of the spinneret plate, so that the fineness of the protofilament is uneven, and defects such as injection heads, filaments and wool are generated, so that the spinneret plate needs to be cleaned regularly.
At present, the spinneret plate is usually inspected by manually observing the cleanliness of the spinneret holes by means of a special microscope. Microscopic impurities can be observed under the amplification effect of the microscope, but micropores on a spinneret plate are more, so that missing detection is easy to occur, and the micropores containing the impurities are difficult to accurately position and have low automation degree. With the development of digital image processing technology, a person skilled in the art tries to obtain an image of a spinneret orifice, obtain an edge profile of the spinneret orifice by morphological processing, calculate the area of the plugged orifice according to the area percentage of closed areas of different curves, further obtain the impurity content, and judge whether impurities are contained or not according to whether the edge profile of the spinneret orifice is circular or not.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a spinneret plate residual impurity detection method based on an image technology.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a spinneret plate residual impurity detection method based on an image technology comprises the following steps:
(1) under the same collection condition (namely under the same conditions of magnification, annular light source and the like, the same collection condition is ensured in order to ensure that the binary image a and the binary image b have comparability), collecting the image of a single spinneret orifice to be detected and carrying out binary processing on the image to obtain a binary image a, collecting the image of a single standard spinneret orifice and carrying out binary processing on the image to obtain a binary image b, wherein the standard spinneret orifice is a spinneret orifice which has the same specification as the spinneret orifice to be detected and does not contain impurities;
(2) denoising the binarized image a and the binarized image b, wherein the denoising process is to remove the area at the periphery of the spinneret orifice, namely, the gray value of the pixel point at the area at the periphery of the spinneret orifice in the binarized image is changed into the value different from the gray value of the pixel point at the area inside the spinneret orifice in the binarized image b, if the binarized image is a Boolean binarized image and the gray value of the pixel point at the area inside the spinneret orifice in the binarized image b is 1, the denoising process is to change the gray value of the pixel point at the area at the periphery of the spinneret orifice in the binarized image into 0; the denoising treatment can avoid interference on subsequent treatment;
(3) adjusting the binary image a obtained in the step (2) to enable the contour boundaries of the spinneret holes in the binary image a and the spinneret holes in the binary image b obtained in the step (2) to be superposed and the two are located at the same position;
(4) calculating impurity content and judging the position of the impurity;
the method for calculating the impurity content comprises the following steps: subtracting the binarized image a obtained in the step (3) from the binarized image b obtained in the step (3), summing matrixes obtained by subtracting to obtain the area of the region occupied by the impurities, and dividing the area by the value obtained by summing the binarized image b obtained in the step (3) to obtain the impurity content;
the method for judging the position of the impurity comprises the following steps:
firstly, respectively selecting points at the same position from the binarized image a obtained in the step (3) and the binarized image b obtained in the step (3) as reference points;
then, acquiring an edge image c of the spinneret orifice in the binarized image a obtained in the step (3), acquiring an edge image d of the spinneret orifice in the binarized image b obtained in the step (3), and selecting a point at the same position on the boundary of the spinneret orifice in the edge image c and the edge image d respectively as a starting point;
and finally, respectively calculating the distances between the reference points in the edge image c and the edge image d and each boundary point on the spinneret orifice from the starting point along the same direction, and calculating the distance daiAnd dbiComparing, judging the position of the impurity according to the comparison result, if more than 5 d are continuously presentaiAnd dbiIf the difference exceeds the threshold, the area surrounded by the connecting line of the starting point and the end point of the pixel points with the continuous difference exceeding the threshold contains impurities, wherein daiIs the distance between the reference point in the edge image c and the ith boundary point, dbiThe distance between a reference point and an ith boundary point in the edge image d is set, i =1, 2.. and n is the number of the boundary points;
the threshold value determining method comprises the following steps: acquiring images of the single reference spinneret orifice with the impurities, which are determined according to the steps (1) to (4) (the images can be manually determined images of the single reference spinneret orifice with the impurities), determining distances between a reference point in an edge image e corresponding to the images and a plurality of boundary points of an area with the impurities (which can be manually marked areas with the impurities), and then averaging to obtain a threshold value, wherein the reference spinneret orifice has the same specification with the spinneret orifice to be detected, the obtaining process of the edge image e is the same as that of the edge image c, and the position of the reference point in the edge image e is the same as that of the reference point in the edge image c.
The method comprises the steps of respectively collecting images of a spinneret orifice to be measured and a standard spinneret orifice, denoising through morphological processing, detecting the outline edge of the spinneret orifice, enabling the two images to be located at the same position, selecting marking points at the same position, sequentially comparing the distances from the marking points to the edge of the spinneret orifice point by point, achieving accurate positioning of impurities, calculating the impurity rate through direct difference of binary images, and being fast and effective in calculation method and wide in application range. In addition, because the invention carries out denoising treatment on the binary image, the closed area outside the spinneret orifice can not influence the result, and the false detection rate is lower.
As a preferred technical scheme:
according to the method for detecting residual impurities of the spinneret plate based on the image technology, in the step (1), the collection condition comprises a magnification factor which is 100-200 times; collecting images of a single spinneret orifice to be detected and images of a single standard spinneret orifice by using a super-depth-of-field microscope; the spinneret orifices to be detected are circular holes, Y-shaped holes or rectangular holes; the threshold value of all binarization processing is 0.4, the threshold value is set in such a way that a binarization image of a spinneret orifice can be completely obtained, if the threshold value is set unreasonably, part of impurities can be removed, and the detection result is influenced; the threshold value of the binarization can be manually set, and can also be automatically obtained by adopting an Otsu threshold value method for processing. The manual setting can set a more appropriate threshold value according to the actual situation of the image.
According to the method for detecting the residual impurities of the spinneret plate based on the image technology, in the step (2), all denoising treatment is performed by adopting a connected domain detection method, compared with other denoising treatment methods, the denoising treatment method provided by the invention can directly remove the regions except the spinneret holes at one time, and the other denoising methods need to adjust parameters and possibly remove the impurities of the spinneret holes.
The method for detecting residual impurities in the spinneret plate based on the image technology specifically comprises the following steps: and searching for connected domains according to the communication of 8, detecting all connected domains in the binary image a and the binary image b, removing the connected domains except the maximum connected domain, and only keeping the spinneret orifice part.
The method for detecting residual impurities in the spinneret plate based on the image technology comprises the following steps of (3): and performing skeletonization processing on the binary image a and the binary image b respectively, detecting the slope of the longest straight line by adopting Hough transformation, calculating the inclination angle according to the slope, and correcting the deviation of the binary image a.
In the method for detecting residual impurities in the spinneret plate based on the image technology, in the step (4), the method for determining the reference point comprises the following steps: and respectively obtaining the minimum external rectangles of the spinneret orifices in the binary image a and the binary image b and solving the central points of the minimum external rectangles, wherein the central points are the reference points.
In the method for detecting residual impurities in the spinneret plate based on the image technology, the binary image a and the binary image b are boolean binary images, the gray value of the area pixel points inside the spinneret hole is 1, the gray value of the area pixel points outside the spinneret hole is 0, and the method for obtaining the minimum circumscribed rectangle of the spinneret hole in the binary image comprises the following steps: and respectively counting the sum of the gray values of the pixel points in the row direction and the sum of the gray values of the pixel points in the column direction of the binary image, wherein the two rows with the gray values of the pixel points first and last not equal to 0 are two horizontal edges of the minimum external rectangle, and the two columns with the gray values of the pixel points first and last not equal to 0 are two vertical edges of the minimum external rectangle.
According to the method for detecting the residual impurities of the spinneret plate based on the image technology, in the step (4), the edge image c and the edge image d are obtained by adopting an edge detection operator; the method for determining the starting point comprises the following steps: and taking the reference point as a starting point, making a vertical upward ray, and taking the intersection point of the ray and the boundary of the spinneret orifice as the starting point.
According to the method for detecting the residual impurities of the spinneret plate based on the image technology, the edge detection operator is a Canny edge detection operator, and the Canny edge detection process comprises the following steps: firstly, smoothing an original image by adopting a Gaussian filter, then calculating the amplitude and the direction of a gradient by adopting finite difference of first-order partial derivatives, then carrying out non-maximum value inhibition on the gradient amplitude, and finally detecting and connecting edges by using a double-threshold algorithm, wherein the double thresholds are 0.6 and 0.24.
Has the advantages that:
the method for detecting the residual impurities of the spinneret plate based on the image technology is simple and convenient to operate, wide in application range, suitable for spinneret holes in various shapes, high in detection accuracy and low in false detection rate, and impurity content and impurity positions can be quickly and efficiently obtained.
Drawings
FIG. 1 is a flow chart of a spinneret plate residual impurity detection method based on image technology;
in fig. 2, (a) is an image of a single spinneret hole to be detected acquired by using a super-depth-of-field microscope, (b) is a binarized image a obtained by binarizing the image of the single spinneret hole to be detected, and (c) is a binarized image a subjected to denoising processing;
in fig. 3, (a) is the binarized image a after skeletonization processing, (b) is the binarized image a after deviation correction, and (c) is the minimum circumscribed rectangle of the binarized image a after deviation correction;
fig. 4 shows an edge image c and distances between an example reference point and boundary points.
Detailed Description
The invention will be further illustrated with reference to specific embodiments. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
A method for detecting residual impurities in a spinneret plate based on an image technology is shown in figure 1 and comprises the following steps:
(1) under the same collection condition (for example, the magnification is 100-200, and an annular light source is adopted), an image of a single spinneret orifice (Y-shaped hole) to be detected (shown in figure 2 (a)) is collected by using an ultra-field-depth microscope and subjected to binarization processing (with the threshold value of 0.4) to obtain a binarization image a (shown in figure 2 (b)), an image of a single standard spinneret orifice is collected and subjected to binarization processing (with the threshold value of 0.4) to obtain a binarization image b, and the standard spinneret orifice is a spinneret orifice which has the same specification as the spinneret orifice to be detected and does not contain impurities;
(2) denoising the binarized image a and the binarized image b by adopting a connected domain detection method (the denoised binarized image a is shown in figure 2 (c)), wherein the denoising treatment is to remove the peripheral area of the spinneret orifice, and the connected domain detection method specifically comprises the following steps: searching for connected domains according to the communication of 8, detecting all connected domains in the binary image a and the binary image b, removing the connected domains except the maximum connected domain, and only keeping the spinneret orifice part;
(3) performing skeletonization on the binarized image a and the binarized image b respectively (the binarized image a after the skeletonization is shown in a figure 3 (a)), detecting the slope of the longest straight line by adopting Hough transformation, calculating the inclination angle according to the slope, and performing deviation rectification on the binarized image a obtained in the step (2) (shown in a figure 3 (b)), so that the contour boundaries of spinneret orifices in the binarized image b obtained in the step (2) are overlapped and are positioned at the same position;
(4) calculating impurity content (namely the ratio of the area of the impurity region to the area of the spinneret orifice), and judging the position of the impurity;
the method for calculating the impurity content comprises the following steps: subtracting the binarized image a obtained in the step (3) from the binarized image b obtained in the step (3), summing matrixes obtained by subtracting to obtain the area of the region occupied by the impurities, and dividing the area by the value obtained by summing the binarized image b obtained in the step (3) to obtain the impurity content;
the method for judging the position of the impurity comprises the following steps:
firstly, respectively selecting points at the same position from the binarized image a obtained in the step (3) and the binarized image b obtained in the step (3) as reference points;
the determination method of the reference point comprises the following steps: respectively obtaining the minimum circumscribed rectangles of the spinneret orifices in the binarized image a and the binarized image b and solving the central point (the minimum circumscribed rectangle of the binarized image a is shown in fig. 3 (c)), wherein the central point is a reference point; the binarization image a and the binarization image b are Boolean type binarization images, the gray value of the area pixel points in the spinneret orifice is 1, the gray value of the area pixel points at the periphery of the spinneret orifice is 0, and the method for acquiring the minimum external rectangle of the spinneret orifice in the binarization image comprises the following steps: respectively counting the sum of gray values of pixel points in the row direction and the sum of gray values of pixel points in the column direction of the binary image, wherein the two rows with the gray values of the pixel points first and last not equal to 0 are two horizontal edges of the minimum external rectangle, and the two columns with the gray values of the pixel points first and last not equal to 0 are two vertical edges of the minimum external rectangle;
then, acquiring an edge image c (shown in fig. 4) of the spinneret orifice in the binarized image a obtained in the step (3) by adopting a Canny edge detection operator, acquiring an edge image d of the spinneret orifice in the binarized image b obtained in the step (3), and selecting points at the same position on the boundaries of the spinneret orifices in the edge image c and the edge image d respectively to be used as starting points;
the method for determining the starting point comprises the following steps: taking the reference point as a starting point, making a vertical upward ray, and taking an intersection point of the ray and the boundary of the spinneret orifice as the starting point;
finally, the distances between the reference points in the edge image c and the edge image d and each boundary point on the spinneret orifice are respectively calculated along the same direction (as shown in figure 4) from the starting point, and d is calculatedaiAnd dbiComparing, judging the position of the impurity according to the comparison result, if more than 5 d are continuously presentaiAnd dbiIf the difference exceeds the threshold, the area surrounded by the connecting line of the starting point and the end point of the pixel points with the continuous difference exceeding the threshold contains impurities, wherein daiIs the distance between the reference point in the edge image c and the ith boundary point, dbiThe distance between a reference point and an ith boundary point in the edge image d is set, i =1, 2.. and n is the number of the boundary points;
the threshold value determining method comprises the following steps: collecting images of a single reference spinneret orifice with impurities, determining the distance between a reference point in an edge image e corresponding to the image and a plurality of boundary points of an area with impurities, and then averaging to obtain a threshold value, wherein the reference spinneret orifice and the standard of the spinneret orifice to be detected are the same, the obtaining process of the edge image e is the same as that of the edge image c, and the position of the reference point in the edge image e is the same as that of the reference point in the edge image c.
According to the method, 30 images of single Y-shaped holes and 1 image of a single standard spinneret hole corresponding to the images are collected to carry out spinneret hole impurity rate and impurity position positioning detection, the actual results (namely the results of manual calculation and marking) of the spinneret hole impurity rate and impurity position positioning are determined, and are compared with the detection results of the spinneret hole impurity rate and impurity position positioning to obtain a false detection rate a, wherein the false detection rate a = number/30 of the images of which the actual results are inconsistent with the detection results, namely the impurity rate is inconsistent and/or the impurity position positioning is inconsistent;
the method comprises the steps of replacing Y-shaped holes in the method with circular holes, collecting images of 30 single circular holes and corresponding images of 1 single standard spinneret hole to carry out spinneret hole impurity rate and impurity position positioning detection, determining actual results (namely results of manual calculation and labeling) of spinneret hole impurity rate and impurity position positioning, and comparing the actual results with detection results of spinneret hole impurity rate and impurity position positioning to obtain a false detection rate b, wherein the false detection rate b = number/30 of images with inconsistent actual results and detection results, and the actual results are inconsistent with the detection results, namely impurity rate and/or impurity position positioning are inconsistent;
adopting a rectangular hole to replace a Y-shaped hole in the method, collecting images of 30 single rectangular holes and corresponding images of 1 single standard spinneret hole to perform spinneret hole impurity rate and impurity position positioning detection, determining actual results (namely results of manual calculation and labeling) of spinneret hole impurity rate and impurity position positioning, and comparing the actual results with detection results of spinneret hole impurity rate and impurity position positioning to obtain a false detection rate c, wherein the false detection rate c = 30 of images/pieces of which the actual results are inconsistent with the detection results, namely the impurity rate is inconsistent and/or the impurity position positioning is inconsistent;
the false detection rate a, the false detection rate b and the false detection rate c are respectively 6.7%, 3.3% and 6.7%, the average false detection rate of the three spinneret orifices is 5.6%, and the false detection rate is far lower than the result of manual detection and the existing image detection method, which shows that the method of the invention has accurate impurity positioning and is beneficial to subsequent impurity cleaning.
Claims (9)
1. A spinneret plate residual impurity detection method based on an image technology is characterized by comprising the following steps:
(1) under the same collection condition, collecting an image of a single spinneret orifice to be detected and carrying out binarization processing on the image to obtain a binarization image a, collecting an image of a single standard spinneret orifice and carrying out binarization processing on the image to obtain a binarization image b, wherein the standard spinneret orifice is a spinneret orifice which has the same specification as the spinneret orifice to be detected and does not contain impurities;
(2) denoising the binary image a and the binary image b, namely removing the peripheral area of the spinneret orifice;
(3) adjusting the binary image a obtained in the step (2) to enable the contour boundaries of spinneret holes in the binary image a to coincide with the contour boundaries of the spinneret holes in the binary image b obtained in the step (2);
(4) calculating impurity content and judging the position of the impurity;
the method for calculating the impurity content comprises the following steps: subtracting the binarized image a obtained in the step (3) from the binarized image b obtained in the step (3), summing matrixes obtained by subtracting to obtain the area of the region occupied by the impurities, and dividing the area by the value obtained by summing the binarized image b obtained in the step (3) to obtain the impurity content;
the method for judging the position of the impurity comprises the following steps:
firstly, respectively selecting points at the same position from the binarized image a obtained in the step (3) and the binarized image b obtained in the step (3) as reference points;
then, acquiring an edge image c of the spinneret orifice in the binarized image a obtained in the step (3), acquiring an edge image d of the spinneret orifice in the binarized image b obtained in the step (3), and selecting a point at the same position on the boundary of the spinneret orifice in the edge image c and the edge image d respectively as a starting point;
and finally, respectively calculating the distances between the reference points in the edge image c and the edge image d and each boundary point on the spinneret orifice from the starting point along the same direction, and calculating the distance daiAnd dbiComparing, judging the position of the impurity according to the comparison result, if more than 5 d are continuously presentaiAnd dbiIf the difference exceeds the threshold, the area surrounded by the connecting line of the starting point and the end point of the pixel points with the continuous difference exceeding the threshold contains impurities, wherein daiIs the distance between the reference point in the edge image c and the ith boundary point, dbiThe distance between a reference point and an ith boundary point in the edge image d is set, i =1, 2.. and n is the number of the boundary points;
the threshold value determining method comprises the following steps: collecting images of a single reference spinneret orifice with impurities, determining the distance between a reference point in an edge image e corresponding to the image and a plurality of boundary points of an area with impurities, and then averaging to obtain a threshold value, wherein the reference spinneret orifice and the standard of the spinneret orifice to be detected are the same, the obtaining process of the edge image e is the same as that of the edge image c, and the position of the reference point in the edge image e is the same as that of the reference point in the edge image c.
2. The method for detecting residual impurities on the spinneret plate based on the image technology as claimed in claim 1, wherein in the step (1), the collection condition comprises a magnification factor, wherein the magnification factor is 100-200 times; collecting images of a single spinneret orifice to be detected and images of a single standard spinneret orifice by using a super-depth-of-field microscope; the spinneret orifices to be detected are circular holes, Y-shaped holes or rectangular holes; the threshold value of all binarization processes was 0.4.
3. The method for detecting residual impurities in the spinneret plate based on the image technology as claimed in claim 1, wherein in the step (2), all denoising processes are performed by a connected domain detection method.
4. The method for detecting residual impurities in the spinneret plate based on the image technology as claimed in claim 3, wherein the connected domain detection method specifically comprises: and searching for connected domains according to the communication of 8, detecting all connected domains in the binary image a and the binary image b, removing the connected domains except the maximum connected domain, and only keeping the spinneret orifice part.
5. The method for detecting residual impurities on the spinneret plate based on the image technology as claimed in claim 1, wherein the step (3) is specifically as follows: and performing skeletonization processing on the binary image a and the binary image b respectively, detecting the slope of the longest straight line by adopting Hough transformation, calculating the inclination angle according to the slope, and correcting the deviation of the binary image a.
6. The method for detecting residual impurities on the spinneret plate based on the image technology as claimed in claim 1, wherein in the step (4), the reference point is determined by: and respectively obtaining the minimum external rectangles of the spinneret orifices in the binary image a and the binary image b and solving the central points of the minimum external rectangles, wherein the central points are the reference points.
7. The method for detecting the residual impurities on the spinneret plate based on the image technology as claimed in claim 6, wherein the binarized image a and the binarized image b are boolean binarized images, the gray value of the area pixel points inside the spinneret hole is 1, the gray value of the area pixel points outside the spinneret hole is 0, and the method for obtaining the minimum circumscribed rectangle of the spinneret hole in the binarized image is as follows: and respectively counting the sum of the gray values of the pixel points in the row direction and the sum of the gray values of the pixel points in the column direction of the binary image, wherein the two rows with the gray values of the pixel points first and last not equal to 0 are two horizontal edges of the minimum external rectangle, and the two columns with the gray values of the pixel points first and last not equal to 0 are two vertical edges of the minimum external rectangle.
8. The method for detecting residual impurities on the spinneret plate based on the image technology as claimed in claim 7, wherein in the step (4), the edge image c and the edge image d are obtained by using an edge detection operator; the method for determining the starting point comprises the following steps: and taking the reference point as a starting point, making a vertical upward ray, and taking the intersection point of the ray and the boundary of the spinneret orifice as the starting point.
9. The method as claimed in claim 8, wherein the edge detection operator is a Canny edge detection operator.
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| CN112630158A (en) * | 2020-12-31 | 2021-04-09 | 常州市新创智能科技有限公司 | Stripping cloth residue detection system and detection method thereof |
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| CN117274965A (en) * | 2023-11-21 | 2023-12-22 | 浙江恒逸石化有限公司 | Training method of image recognition model, spinneret plate detection method and device |
| CN117274965B (en) * | 2023-11-21 | 2024-03-05 | 浙江恒逸石化有限公司 | Training method of image recognition model, spinneret plate detection method and device |
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